From 4f052a259297c546f312ea1e4af912a6ee502d09 Mon Sep 17 00:00:00 2001
From: Joe <127773439+joegeorge022@users.noreply.github.com>
Date: Fri, 20 Dec 2024 19:22:34 +0530
Subject: [PATCH] Add files via upload

---
 Day-16/Indhu Subash.ipynb | 98 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 98 insertions(+)
 create mode 100644 Day-16/Indhu Subash.ipynb

diff --git a/Day-16/Indhu Subash.ipynb b/Day-16/Indhu Subash.ipynb
new file mode 100644
index 0000000..cec8d76
--- /dev/null
+++ b/Day-16/Indhu Subash.ipynb	
@@ -0,0 +1,98 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# This is a sample Jupyter Notebook\n",
+    "\n",
+    "Below is an example of a code cell. \n",
+    "Put your cursor into the cell and press Shift+Enter to execute it and select the next one, or click 'Run Cell' button.\n",
+    "\n",
+    "Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.\n",
+    "\n",
+    "To learn more about Jupyter Notebooks in PyCharm, see [help](https://www.jetbrains.com/help/pycharm/ipython-notebook-support.html).\n",
+    "For an overview of PyCharm, go to Help -> Learn IDE features or refer to [our documentation](https://www.jetbrains.com/help/pycharm/getting-started.html)."
+   ],
+   "id": "8a77807f92f26ee"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-12-20T12:21:53.769586Z",
+     "start_time": "2024-12-20T12:21:53.744373Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "\"\"\"\n",
+    "AUTHOR : INDHU SUBASH\n",
+    "DATE : 20-12-2024\n",
+    "\"\"\"\n",
+    "student_ids = [102, 101, 105, 102, 101, 103, 104, 105]\n",
+    "unique_sorted_ids = sorted(set(student_ids))\n",
+    "unique_sorted_ids=set(unique_sorted_ids)\n",
+    "print(\"Unique and Sorted Student IDs:\", unique_sorted_ids)\n",
+    "\n",
+    "grades = (100,98,95,87,93)\n",
+    "average_grade = sum(grades) / len(grades)\n",
+    "print(f\"Grades : {grades}\")\n",
+    "print(\"Average Grade:\", average_grade)\n",
+    "\n",
+    "python_students = {\"Appu\", \"Abhijith\", \"Unni\", \"Abhishek\"}\n",
+    "machine_learning_students = {\"Unni\", \"Eve\", \"Abhishek\", \"Alice\"}\n",
+    "\n",
+    "common_students = python_students & machine_learning_students\n",
+    "print(\"Students attending both workshops:\", common_students)\n",
+    "\n",
+    "student_grades = {\n",
+    "    \"Appu\": (85, 90, 78),\n",
+    "    \"Abhijith\": (88, 76, 92),\n",
+    "    \"Unni\": (80, 85, 88),\n",
+    "}\n",
+    "\n",
+    "for student, grades in student_grades.items():\n",
+    "    average = sum(grades) / len(grades)\n",
+    "    print(f\"{student}'s Average Grade: {average:.2f}\")\n"
+   ],
+   "id": "fbc121e30a2defb3",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Unique and Sorted Student IDs: {101, 102, 103, 104, 105}\n",
+      "Grades : (100, 98, 95, 87, 93)\n",
+      "Average Grade: 94.6\n",
+      "Students attending both workshops: {'Abhishek', 'Unni'}\n",
+      "Appu's Average Grade: 84.33\n",
+      "Abhijith's Average Grade: 85.33\n",
+      "Unni's Average Grade: 84.33\n"
+     ]
+    }
+   ],
+   "execution_count": 1
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}